| Volatile organic compounds (VOCs) is one of the key precursors of ozone and secondary organic aerosol formation, and accurate estimation in their emissions plays a crucial role in air quality simulations and policy making. However, the current VOCs emission inventories at nation level show shortages in reflecting emission characteristics in small-scale regions and do not perform well when used in high-resolution air quality modeling. This study developed high-resolution anthropogenic VOCs emission inventories for Jiangsu Province from 2005 to 2014, based on detailed local emission source information and the results of field measurements on chemical industry emission profiles. Moreover the sector and spatial distribution, species profiles, atmospheric oxidation activities and inter-annual variabilities of emissions were analyzed.56 VOCs samples were collected in 9 chemical plants, and then analyzed by gas chromatography-mass spectrometry (GC-MS).VOCs profiles of nine chemical products (synthetic rubber, acetate fiber, polyether, vinyl acetate, ethylene, butanol and octanol, propylene epoxide, polyethylene and glycol) were obtained.Results of inventories showed that VOCs emissions increased from 1770 Gg in 2005 to 2510 Gg in 2014. Emissions from industrial processes and solvent increased respectively from 461 Gg to 958 Gg and from 380 Gg to 966 Gg. With high oxidation capability, alkanes, aromatics and oxygenated VOCs (OVOCs) were the most important species of VOCs emissions, accounting for 25.9%-29.9%,20.8%-23.2% and 18.2%-21.0% to total emissions respectively. The ozone formation potentials (OFPs) of emissions increased from 3880 Gg to 5200 Gg during 2005 to 2014. The spatial distribution of emissions indicated that high emission density mainly appeared in urban areas of developed cities (Nanjing, Suzhou, Wuxi, etc.) in southern Jiangsu. The uncertainties of annual VOCs emissions vary from years, and the result for 2014 is -41%-+93%, expressed as 95% confidence intervals.The comparisons of emission estimates based on different sources of activity data indicated that the emission results based on statistical yearbooks omitted or underestimated the emissions from sources like ceramic industry, glass fiber production and chemical industry. Compared to other studies, the total VOCs emissions of this study were a little higher than most other emission inventories, and significant discrepancies existed in sector distribution and spatial distribution. The differences of sector distribution were attributed partly to the inclusion of certain sources (ceramics, fermentation alcohol and cooking, etc) omitted by some other studies and the consideration of local condition of Jiangsu Province for determination of parameters relevant to emission calculation (e.g., vehicle kilometers travled and application rates of wate-based paint, etc). Large uncertainties in VOCs emission inventories also contributed to the discreapancy. Compared with Multi-resolution Emission Inventory for China (MEIC), notable higher emission densities in this study were found in areas where large point sources were located, and significant lower emission density were detected in the central urban areas of Nanjing, Wuxi and Xuzhou. This indicated that MEIC failed to capture the impact of point sources on the spatial distribution of emissions and may overestimate the emission level in central urban areas, due to the use of GDP/population as proxies to allocate emssions. The VOCs emission results by species of atmospheric chemistry mechanism CB05 and SAPRC99 of this study showed significant differences compared with MEIC. The difference of specie OLE1 were caused by the update of profile for architecture paint use, and the differences of other species were due to the discreapancy in sector distribution. |
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